Person tagging in image processing systems refers generally to the process of characterizing a person observed in an image or sequence of images of a video signal, and using the characterization to determine if the same person is present in one or more subsequent images. A detected person is “tagged” by association with the characterization, and can thereby be identified as the tagged person in subsequent images. The process of person tagging is thus distinct from a person recognition process in that it does not necessarily involve definitive identification of a given person as being a particular known individual. Instead, it simply generates an indication that a person in a current image is believed to match a person detected in a previous image. The person tagging process is also referred to as person matching.
Conventional person tagging generally involves the use of either appearance-based or geometry-based detection algorithms. The appearance-based algorithms include techniques such as template matching and color histograms. Examples of features used in geometry-based algorithms include size, shape, etc. The conventional techniques, however, have been unable to combine appearance and geometric features in a manner which provides more efficient and effective person tagging for an image processing system.